Multispectral image fusion technique based on decoupling of information

被引:0
|
作者
Yu, Wenqi [1 ]
Wang, Huilin [1 ]
Liu, Jilong [1 ]
Wang, Guan [1 ]
机构
[1] Xian Inst Appl Opt, Xian 710065, Shaanxi, Peoples R China
基金
中国国家自然科学基金;
关键词
image fusion; image matching; image processing; NETWORK; NEST;
D O I
10.1049/ipr2.13296
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
To address the issue of unremarkable targets and the serious loss of background details that occurs in multispectral image fusion, a multispectral image fusion method based on information decoupling is proposed. In accordance with the U-shaped network structure, multi-scale feature fusion is employed to obtain comprehensive contextual features. Subsequently, taking into account the differences between base and texture information in the images, the recovered image is reconstructed by fusing feature information through the information decoupling branches. Finally, the information decoupling is supervised by a loss function. In addition, a series of comparative experiments are conducted on a self-constructed multispectral dataset and a publicly available dataset. Experimental results demonstrate that our method not only achieves higher fusion accuracy but also has superior visualization results.
引用
收藏
页数:14
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